code: def _squared_error(x, y, scale, mask):
      diff = x - y
      if getattr(scale, "shape", ()) or getattr(mask, "shape", ()):
          error = torch.einsum("nbe,nbe->nb", diff, diff)
          return scale_and_mask(error, scale, mask).sum(-1)
      else:
          error = torch.einsum("nbe,nbe->n", diff, diff)
          return scale_and_mask(error, scale, mask)
  
file_path: pyro/pyro/infer/energy_distance.py
imports: import operator
  from collections import OrderedDict
  from functools import reduce
  import torch
  import pyro
  import pyro.poutine
  from pyro.distributions.util import scale_and_mask
  from pyro.infer.elbo import ELBO
  from pyro.infer.util import is_validation_enabled, validation_enabled
  from pyro.poutine.util import prune_subsample_sites
  from pyro.util import check_model_guide_match, check_site_shape, warn_if_nan
label_desc: Use image node_id 1 for calling a global function with example usage: _squared_error(x, y, scale, mask) and returns: scale_and_mask, scale_and_mask